VISCERAL Silver Corpus

Since the original host page (https://visceral.eu/benchmarks/anatomy3-open/) is no longer accessible, we have obtained permission from the original authors and affiliated institutions and plan to re-release the VISCERAL dataset in CADS, including its original images and annotations. We are currently in the process of obtaining renewed ethics approval, and the dataset will be made publicly available once approved.

License

TBD

Citation

Paper BibTeX:

@inproceedings{krenn2015creating,
  title={Creating a large-scale silver corpus from multiple algorithmic segmentations},
  author={Krenn, Markus and Dorfer, Matthias and Jim{\'e}nez del Toro, Oscar Alfonso and M{\"u}ller, Henning and Menze, Bjoern and Weber, Marc-Andre and Hanbury, Allan and Langs, Georg},
  booktitle={International MICCAI Workshop on Medical Computer Vision},
  pages={103--115},
  year={2015},
  organization={Springer}
}

Dataset description

Homepage: https://visceral.eu/benchmarks/anatomy3-open/ (currently down)

Number of CT volumes: 127

Contrast: Unenhanced whole-body CT and contrast-enhanced abdomen and thorax CT (iodine-based contrast agent)

CT body coverage: Whole-body (head to knee) and contrast-enhanced regions (corpus mandibulae to pelvis)

Does the dataset include any ground truth annotations?: Yes

Original GT annotation targets: Liver, spleen, pancreas, gallbladder, urinary bladder, aorta, trachea, right lung, left lung, sternum, thyroid gland, first lumbar vertebrae, right kidney, left kidney, right adrenal gland, left adrenal gland, right psoas major, left psoas major, right rectus abdominis, left rectus abdominis

Number of annotated CT volumes: 127

Annotator: Label fusion of multiple algorithms (k-means clustering, rule-based segmentation, multi-boost learning SSM search, multi-atlas registration)

Acquisition centers: Medizinische Universität Wien (MUW), Universitätsklinikum Heidelberg (UKL-HD), Agència d‟Avalució, I Qualitat en Salut (GENCAT) in Catalonia Spain.

Pathology/Disease: Whole-body: bone marrow neoplasms (e.g., multiple myeloma). Contrast-enhanced: malignant lymphoma.

Original dataset download link: -

Original dataset format: nifti